The Motion-Based Gaming Peripheral Management (MBP-M) Framework for Robust and Accurate Program-Device Interaction

In recent years, a tremendous rise in consumer grade electronics has afforded bountiful opportunities for quantification and instrumentation of the human body, particularly through the use of motion-based gaming peripherals. Unfortunately, developing applications capable of reliably and robustly collecting data from such devices involves non-trivial complexities that must be accounted for. To combat these complexities, this thesis describes the Motion Based Gaming Peripherals Management (MBP-M) Framework. When integrated inside a program, the framework controls all device and data handling, thereby allowing developers to focus entirely on the intended use of device data. Explored in the thesis are examples of the use of gaming peripherals in non-gaming efforts and the core guiding principles, architecture, and data processing flow of the framework. Additionally, results of performance tests demonstrating the efficacy of the framework are presented and discussed, showing that the MBP-M Framework performs reliably and robustly and adheres to the guiding principles.